Entity extraction: From unstructured text to DBpedia RDF triples

Summary, in English

In this paper, we describe an end-to-end system that automatically extracts RDF triples describing entity relations and properties from unstructured text. This system is based on a pipeline of text processing modules that includes a semantic parser and a coreference solver. By using coreference chains, we group entity actions and properties described in different sentences and convert them

into entity triples. We applied our system to over 114,000 Wikipedia articles and we could extract more than 1,000,000 triples. Using an ontology-mapping system that we bootstrapped using existing DBpedia triples, we mapped 189,000 extracted triples onto the DBpedia namespace. These extracted entities are availableonline in the N-Triple format. 1



1 http://semantica.cs.lth.se/

• Author: Peter Exner; Pierre Nugues
• Department/s: Department of Computer Science; ELLIIT: the Linköping-Lund initiative on IT and mobile communication; Robotics and Semantic Systems
• Publishing year: 2012
• Language: English
• Pages: 58-69
• Publication/Series: Proceedings of the Web of Linked Entities Workshop in conjuction with the 11th International Semantic Web Conference (ISWC 2012)
• Full text: - 607 kB; Download statistics
• Links: http://ceur-ws.org/Vol-906/paper7.pdf
• Document type: Conference paper
• Publisher: CEUR-WS
• Topic: Computer Science
• Conference name: The Web of Linked Entities Workshop (WoLE 2012)
• Conference date: 2012-11-11
• Conference place: Boston, United States
• Status: Published
• ISBN/ISSN/Other: ISSN: 1613-0073